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FlowPipe: LLM-Enhanced Conditional Generative Flow Networks for Data Preparation Pipeline Construction

Summary: FlowPipe casts data-preparation pipeline synthesis as conditional flow generation, using trajectory balance, FiLM-modulated LLM priors, and failure-aware pruning to improve credit assignment and exploration. Across 74 datasets, it boosts accuracy 11.96% and converges 12.5× faster than SOTA baselines. (summarized by gpt-6-luna on Oct 22 2026)

Paper ID
h29be59f69716aba2
Venue
SIGMOD
Year
2027
Pagerank
4.9605343e-05
Overall Rank
10,397 | 30.31%
DOI
10.1145/3837112
PDF
Download (CC BY 4.0)

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Authors

BibTeX Citation

@inproceedings{ni_sigmod27,
        title = {{FlowPipe: LLM-Enhanced Conditional Generative Flow Networks for Data Preparation Pipeline Construction}},
        author = {Ni, Kunyu and Cao, Lei and He, Jie and Zhang, Xiaotong and Jin, Jianfeng and Dong, Junyu and Yu, Yanwei},
        series = {{SIGMOD} '27},
        booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
        publisher = {Association for Computing Machinery},
        doi = {10.1145/3837112},
        url = {https://dl.acm.org/doi/10.1145/3837112},
        year = {2027}
}

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Outgoing Citations (Sorted by Pagerank)

Showing 15 of 15 cited papers.

Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.

Rank Cited Paper Year Venue Pagerank
323 Can Foundation Models Wrangle Your Data? 2023 VLDB 0.00021022156
948 Democratizing Data Science through Interactive Curation of ML Pipelines 2019 SIGMOD 0.00012900728
989 Data Cleaning: Overview and Emerging Challenges 2016 SIGMOD 0.00012638176
1,278 Automating Large-Scale Data Quality Verification 2018 VLDB 0.00011208469
1,306 Detecting Data Errors: Where are we and what needs to be done? 2016 VLDB 0.00011076619
1,616 SystemDS: A Declarative Machine Learning System for the End-to-End Data Science Lifecycle 2020 CIDR 0.00010048776
1,669 Table-GPT: Table Fine-tuned GPT for Diverse Table Tasks 2024 SIGMOD 9.9157758e-05
2,116 Production Machine Learning Pipelines: Empirical Analysis and Optimization Opportunities 2021 SIGMOD 9.0047829e-05
3,970 DiffPrep: Differentiable Data Preprocessing Pipeline Search for Learning over Tabular Data 2023 SIGMOD 6.8768492e-05
4,005 Auto-Pipeline: Synthesizing Complex Data Pipelines By-Target Using Reinforcement Learning and Search 2021 VLDB 6.8448428e-05
5,230 Saga: A Scalable Framework for Optimizing Data Cleaning Pipelines for Machine Learning Applications 2023 SIGMOD 6.2059854e-05
5,466 HAIPipe: Combining Human-generated and Machine-generated Pipelines for Data Preparation 2023 SIGMOD 6.1038307e-05
6,438 CtxPipe: Context-aware Data Preparation Pipeline Construction for Machine Learning 2024 SIGMOD 5.7678369e-05
7,227 WindTunnel: Towards Differentiable ML Pipelines Beyond a Single Model 2022 VLDB 5.5647576e-05
9,842 CatDB: Data-catalog-guided, LLM-based Generation of Data-centric ML Pipelines 2025 VLDB 5.1064323e-05
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